Emergent Mind
Statistically and Computationally Efficient Variance Estimator for Kernel Ridge Regression
(1809.06019)
Published Sep 17, 2018
in
math.ST
,
cs.LG
,
stat.ML
,
and
stat.TH
Abstract
In this paper, we propose a random projection approach to estimate variance in kernel ridge regression. Our approach leads to a consistent estimator of the true variance, while being computationally more efficient. Our variance estimator is optimal for a large family of kernels, including cubic splines and Gaussian kernels. Simulation analysis is conducted to support our theory.
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